Connectivism

Connectivism is a hypothesis of learning which emphasizes the role of social and cultural context. In this sense, Connectivism proposes to see knowledge's structure as a network and learning as a process of pattern recognition. Connectivism is often associated with and proposes a perspective similar to Vygotsky's 'zone of proximal development' (ZPD), an idea later transposed into Engeström's (2001) Activity theory. The relationship between work experience, learning, and knowledge, as expressed in the concept of ‘connectivity, is central to connectivism, motivating the theory's name. What sets connectivism apart from theories such as constructivism is the view that "learning (defined as actionable knowledge) can reside outside of ourselves (within an organization or a database), is focused on connecting specialized information sets, and the connections that enable us to learn more are more important than our current state of knowing".

The phrase "a learning theory for the digital age" indicates the emphasis that connectivism gives to technology's effect on how people live, communicate and learn.

The central aspect of connectivism is the metaphor of a network with nodes and connections. In this metaphor, a node is anything that can be connected to another node such as an organization, information, data, feelings, and images. Connectivism recognizes three node types: neural, conceptual (internal) and external. Connectivism sees learning as the process of creating connections and expanding or increasing network complexity. Connections may have different directions and strength. In this sense, a connection joining nodes A and B which goes from A to B is not the same as one that goes from B to A. There are some special kinds of connections such as "self-join" and pattern. A self-join connection joins a node to itself and a pattern can be defined as "a set of connections appearing together as a single whole".

The idea of organisation as cognitive systems where knowledge is distributed across nodes originated from the Perceptron (Artificial neuron) in an Artificial Neural Network, and is directly borrowed from Connectionism, "a software structure developed based on concepts inspired by biological functions of brain; it aims at creating machines able to learn like human".

The network metaphor allows a notion of "know-where" (the understanding of where to find the knowledge when it is needed) to supplement to the ones of "know-how" and "know-what" that make the cornerstones of many theories of learning.

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